[Spatial-temporal Evolution and Regional Differences of Synergistic Effect of Green and Low-carbon Energy Transformation and Pollution Reduction and Carbon Reduction in the Yangtze River Economic Belt].

The synergistic enhancement of pollution and carbon reductions serves as a primary lever for promoting the comprehensive green transformation of economic and social development， with energy being a crucial battleground for this green transition. In this study， we conduct an in-depth exploration of the strategic implications of green and low-carbon energy transition and pollution and carbon reductions. We construct an evaluation index system for green and low-carbon energy transition and pollution and carbon reductions. We employ a combination of the entropy weight method， Kernel density estimation， composite system synergy model， Theil index， and spatial Markov chain methods to empirically analyze the regional disparities and dynamic evolutionary characteristics of the synergistic effects of green and low-carbon energy transition and pollution and carbon reductions in the Yangtze River Economic Belt from 2010 to 2022. The results indicated that： ① Both the green and low-carbon energy transition index and the pollution and carbon reduction index have shown a steady growth trend， with the gap in green and low-carbon energy transition levels among provinces gradually widening， while the gap in pollution and carbon reduction levels first narrowed and then widened. ② The level of synergistic development between the green and low-carbon energy transition and pollution and carbon reductions significantly increased， with the overall coordination level demonstrating a dynamic process from mild incoordination to mild coordination and then to moderate coordination and a spatial distribution situation of "high on both sides， low in the middle" gradually emerging regionally. ③ The overall disparity in synergistic levels first rose and then fell， with the contribution rate showing that before 2017， it was mainly due to differences within regions， and after 2018 it was mainly due to differences between regions. The overall difference values by region were as follows： midstream areas > upstream areas > downstream areas. ④ The probability of upward transition was highest for low synergy levels， followed by moderate synergy levels； considering the impact of spatial neighborhood factors， neighborhoods with low synergy levels could hinder the development of local synergy types to some extent， while neighborhoods with higher synergy levels could have a pulling effect on the local area. Finally， some suggestions are put forward， such as increasing the policy inclination and technical support for areas with a low level of synergy and strengthening the radiation demonstration role of areas with high level of synergy.